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Neural Computing and Applications

, Volume 29, Issue 10, pp 823–836 | Cite as

pth Moment synchronization of Markov switched neural networks driven by fractional Brownian noise

  • Xianghui Zhou
  • Jun Yang
  • Zhi Li
  • Dongbing Tong
Original Article
  • 233 Downloads

Abstract

This paper deals with the pth moment synchronization problem for a type of the stochastic neural networks with Markov switched parameters and driven by fractional Brownian noise (FBNSNN). A method called time segmentation method, very different to the Lyapunov functional approach, has been presented to solve the above problem. Meanwhile, based on the trajectory of error system, associating with infinitesimal operator theory, we propose a sufficient condition of consensus for the drive–response system. The criterion of pth moment exponential stability for FBNSNN can guarantee the synchronization under the designed controller. Finally, two numerical examples and some illustrative figures are provided to show the feasibility and effectiveness for our theoretical results.

Keywords

Synchronization pth Moment Time segmentation Switched neural networks Fractional Brownian noise 

Notes

Acknowledgments

This work is partially supported by the Open Research Fund Program of Institute of Applied Mathematics Yangtze University (Grant No. KF1602).

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Copyright information

© The Natural Computing Applications Forum 2016

Authors and Affiliations

  • Xianghui Zhou
    • 1
  • Jun Yang
    • 2
  • Zhi Li
    • 1
  • Dongbing Tong
    • 3
  1. 1.School of Information and MathematicsYangtze UniversityJingzhouChina
  2. 2.School of Mathematics and StatisticsAnyang Normal UniversityAnyangChina
  3. 3.College of Electronic and Electrical EngineeringShanghai University of Engineering ScienceShanghaiChina

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